similar to: Bonferroni with unequal sample sizes

Dear all, I am trying to run Wilcoxon Rank-Sum Test with Bonferroni's correction. I have two lists: l0, l1: mapply(function(x,y)wilcox.test(x,y)$p.value, l0, l1) How do I run Bonferroni's correction on mapply? Any help is much apperciated. Thanks, -Raj

# R for Windows will not send your bug report automatically. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs at r-project.org # ###################################################### This report is joint from Richard Heiberger <rmh at temple.edu> and Burt Holland <bholland at temple.edu>. Burt Holland is the coauthor

Dear R-help, I have a question about pairwise.t.test and adjustment for multiple comparisons for paired data points. I have the following data: n=c("x", "x", "x", "x", "x", "x", "x", "x", "x", "x", "y", "y", "y", "y", "y", "y",

Hi! I need to run a wilcoxon (Mann-whitly, in fact) test with bonferroni correction, as I am running 10 consecutive wilcoxon test not independent, and I know that bonferroni will partially correct for this problem, but I have no idea how to do it with R, I have been looking in the archive but couldn't understand how to do it. The format I am using at the moment is r4_o <- [1]

Hi, I'm having no luck figuring out how to find Bonferroni simultaneous confidence intervals to obtain a family of estimates in R. Does anyone know how to do this? Thank you!

I am performing a sequential bonferroni adjustment on the results of an ANCOVA but the equation I have for calculating p-values from the t-values is not working. I can't seem to find it anywhere else. This is the code I have now: 2*(1-pt(t,df)) where t=t-value and df=degrees of freedom from the ANCOVA. Is there an error in the code? maybe another way to find the p-values? Help! -- View this

Please can someone advise me how I can adjust correlations using bonferroni's correction? I am doing manny correlation tests as part of an investigation of the validity/reliability of a psychometric measure. Help would be so appreciated! Cheers, Louise

Hello. We have a question concerning the nonparametric analysis of a dataset, which resulted in rejection of the null hypothesis (Kruskal-Wallis-test = H-test). In order to find out which sample means actually are statistically different, we want to do multiple comparisons with the Wilcoxon rank sum test (= U-test); the p-level should be corrected according to Bonferroni-Holm. Thus we decided to

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

Hola a todos/as estoy analizando un diseño factorial con una variable intrasujeto y una inter-sujeto. Ambas resultan significativas en el anova y quiero hacer un análisis por pares, pero aún no sé como puedo hacerlo en R. Me interesan ambos Bonferroni y Tukey. ¿Alguien podría indicarme? Gracias [[alternative HTML version deleted]]

I have created an xyplot of a time series with the following code... win.graph(width = 10, height = 7) panel1 = function(x, y) { panel.loess(x, y, lwd=2.5, span=0.5, col="gray") panel.xyplot(x, y, pch=19, col="blue", cex=1.25) } xyplot(oneplusdensity ~ year, data=figdata, aspect="fill", cex=1.5, xlab=NULL, ylab=expression("Crabs per

I am trying to import data from a SAS XPORT file that contains 24 SAS files. When I use the "read.xport" procedure only about 16 data frames (components) are created. Any suggestions? ************************************************************************* Gary A. Nelson, Ph.D Massachusetts Division of Marine Fisheries 30 Emerson Avenue Gloucester, MA 01930 Phone: (978)

Hi! I have been working several years with R but it's my first public question. I hope I'll be clear :) . This question is related to obtaining letter-based representation of non-parametric pairwise comparisons. I have a dataframe with this structure (but with quite more rows and cols): A B C factor 1 2 2 one 2 1 2 one 2 2 3 two 2 3 2 two 1 4 2 three 9 8 1 three I have no normality,

While building a package, I see the following: * checking R code for possible problems ... NOTE cheat.fit: no visible binding for global variable 'Zobs' plot.jml: no visible binding for global variable 'Var1' I see the issue has come up before, but I'm having a hard time discerning how solutions applied elsewhere would apply here. The entire code for both functions is below,

Dear All., I've created R-code for which a user will be asked to choose between 2 analyses. I've written one function for each type of analysis. Within each function, the users is prompted to enter information. An example is: cat("Enter value for lower Linf :\n") L1<-scan(n=1) cat("Enter value for upper Linf :\n") L2<-scan(n=1)

Well fellow R users, I throw myself on your mercy. Help me, the unworthy, satisfy my employer, the ungrateful. My feeble ramblings follow... I've searched R-Help, the R Website and done a GOOGLE without success for a one way ANOVA procedure to analyse data that are both non-normal in nature and which exhibit unequal variances and unequal sample sizes across the 4 treatment levels. My

Hi, all: Two examples are shown below. I want to use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in front of the

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,1]<--1 m[8,9]<-1

I need to do a somewhat complex rearrangement of an existing dataframe that involves an "on-the-fly" conditional summary as well. I've tried to make the example as simple as possible. Code to produce the object being acted on is at the end of the message. I hope this isn't too much for a single posting. Any guidance will be much appreciated. The input example looks like

Dear R-users, In a randomized placebo-controlled within-subject design, subjects recieved a psycho-active drug and placebo. Subjects filled out a questionnaire containing 15 scales on four different time points after drug administration. In order to detect drug effects on each time point, I compared scale values between placebo and drug for all time conditions and scales, which sums up to